Metabolic syndrome is a group of metabolic abnormalities that includes elevated serum triglycerides, low level of high-density lipoprotein, high blood pressure, large waist circumference, microalbuminuria and impaired glucose tolerance. It affects more than half of older adults in the U.S. The syndrome, defined as having 3 or more of the abnormalities, increases the risk of chronic diseases, most notably cardiovascular disease. Recent cross-sectional studies link the syndrome to higher periodontal disease prevalence. Prospective studies are needed to further understand the relationship between metabolic syndrome and periodontal disease. Metabolic syndrome is a progressive disorder. Although 3 or more components must be present for a positive diagnosis, not all components will necessarily develop at the same time. Furthermore, the directionality of the association has not been established; metabolic syndrome may be a predictor or a complication of periodontal disease. We maintain that the sequence of appearance and duration of the different metabolic syndrome components, rather than a yes/no diagnosis, need be examined in relation to periodontal disease incidence and progression. This study proposes to perform secondary data analyses of available oral health, body fatness, medical examination, laboratory and dietary data from a unique cohort of 750 men who have been followed up to 30 years in the Department of Veterans Affairs Dental Longitudinal Study. The men are not VA patients, but are volunteers who receive medical and dental care from the private sector. The key periodontal disease indices we will examine are radiographic alveolar bone loss, probing pocket depth, and clinical attachment loss, which have been measured on each tooth approximately every 3 years. Additional oral health measures include bleeding on probing, tooth mobility, plaque, calculus and decay/restorations on each tooth. Serum lipids, fasting serum glucose, body mass index and waist circumference were also measured every 3 years over the same time period. The primary longitudinal statistical analyses will be performed with generalized linear mixed models that incorporate duration of the various metabolic syndrome components into the independent variables to predict periodontal disease and control for important confounding factors. To address the directionality of the association, we will compare models with periodontal disease measures as the outcomes to models with metabolic syndrome as the outcome. The generalized linear mixed models will be followed up with structural equation models to estimate the relative contribution of each potential step in pathways linking metabolic syndrome and periodontal disease. For our third aim, we will examine whether the addition or substitution of periodontal disease status for one or more of the metabolic syndrome components improves the prediction of cardiovascular disease risk compared to the current syndrome definition. This proposed epidemiologic study is a timely and cost-effective means to better understand the relationship between periodontal disease and the metabolic syndrome.